How to Create AI Apps Using LLaMA 3 API

LLaMA 3 excels in benchmarks with larger model size and diverse training data, rivaling ChatGPT and Gemini.

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How to Create AI Apps Using LLaMA 3 API

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Creating an AI app with LLaMA 3 API, especially for those aiming to simplify their digital tasks or enhance their tech arsenal, is a journey paved with innovation and creativity. stands out as the cornerstone for this endeavor, offering a no-code solution that dramatically lowers the barrier to entry for AI-driven application development.

Artificial Intelligence (AI) is transforming our world, and with platforms like LLaMA 3 API, creating your AI app has never been more accessible. With this guide, you'll learn how to build an app using LLaMA 3 API, even if you have little to no coding experience. Whether you're an aspiring developer, a business professional curious about AI, or simply an individual with a creative idea, this step-by-step tutorial will set you on the path to making your own AI app.

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Meta Llama 3 is a powerful open-source AI assistant that can help with a wide range of tasks like learning, coding, creative writing, and answering questions.
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What is LLaMA 3 API

Meta's most recent open-source large language model (LLM) family, LLaMA 3 (Language Model for Assisted Annotation), follows in the footsteps of LLaMA 2. It showcases top-notch performance on multiple benchmarks and adds features like improved reasoning and an 8,000-token context window, which is twice as big as LLaMA 2.

The "Instruct" models in Meta's four LLaMA 3 releases to date have been fine-tuned to better obey human directions. These versions include 8B, 8B-Instruct, 70B, and 70B-Instruct.

A version with 400B parameters is currently being worked on.
The most important thing about LLaMA 3 is that, unlike proprietary models like GPT-4 and Google’s Gemini, Meta has made it publicly available for research and commercial uses.

Companies like Groq, Databricks, and Replicate provide APIs that developers and corporations may use to access and modify the model.

These vendors facilitate the deployment and integration of LLaMA 3 into applications through their managed APIs and services, which make possible capabilities such as:
Personalized domain-specific experiences through the usage of private data
Reduced lag time and enhanced performance
Complete compatibility with preexisting processes and systems

To sum up, the LLaMA 3 API is a collection of cloud services that developers and corporations may use to access Meta's open-source language model, which is powerful and can be used in applications on a large scale.

What Makes LLaMA So Special

The essence of LLaMA's uniqueness lies in its blend of accessibility, power, and innovation. It's not just another AI model; LLaMA represents a leap towards democratizing AI, making advanced technologies available to a wider audience. By being open-source, it invites collaboration and development across diverse fields, fostering a community of creators who can push the boundaries of what AI can do. Its architecture, designed for efficiency and adaptability, ensures that LLaMA is not only a tool for today but a foundation for the future of AI applications.

What Makes LLaMA 3 Unique: Its Unparalleled Features

  • Open-Source Accessibility: LLaMA is available to anyone, promoting innovation and collaboration among developers, researchers, and hobbyists.
  • Adaptable for Various Applications: Whether for language translation, content generation, or more complex tasks, LLaMA's versatile architecture supports a wide range of uses.
  • Community-Driven Development: By being open-source, it benefits from contributions that enhance its capabilities and keep it on the cutting edge of AI technology.
  • Resource Efficiency: LLaMA is designed to be resource-efficient, allowing for deployment in various environments, including those with limited computing power.

Is LLaMA 3 Better Than ChatGPT and Gemini?

Whether LLaMA 3 is better than ChatGPT and Gemini largely depends on specific use cases and preferences. Llama 3's open-source nature and adaptability might offer distinct advantages in research and development settings, fostering innovation and collaboration. Meanwhile, ChatGPT and Gemini might excel in particular applications or usability aspects. The choice between these models should be guided by the specific requirements, such as the desired application, ease of use, and support for customization.


  • Meta claims that LLaMA 3 8B outperforms open-source models like Mistral 7B and Gemma 7B on 9 benchmarks including MMLU, ARC, and DROP.
  • LLaMA 3 70B surpasses Gemini 1.5 Pro on benchmarks like MMLU, HumanEval, and GSM-8K, though it doesn't quite match Anthropic's Claude 3 Opus.
  • On Meta's custom test set covering coding, writing, reasoning, and summarization, LLaMA 3 70B outperformed Mistral Medium, GPT-3.5, and Claude Sonnet.
Llama 3 banchmarks

Model Size and Training Data:

  • With 70B parameters and training on 15 trillion tokens (750 billion words), LLaMA 3 70B has a larger model size and more diverse training data compared to models like GPT-3.5 and Gemini 1.5 Pro.
  • The larger model size and training data could give LLaMA 3 an edge in areas like reasoning, coding, and handling complexity.


  • Meta claims LLaMA 3 offers improved "steerability", lower refusal rates, and higher accuracy on trivia, history, STEM fields, and coding recommendations compared to previous versions.
  • Upcoming larger versions of LLaMA 3 (over 400B parameters) are expected to further enhance performance, reasoning abilities, and support multimodal inputs like images and audio.

Step-by-Step Guide to Building Your AI App with LLaMA 3 API

Follow these detailed steps to create your own AI app using the powerful LLaMA 3 API.

Step 1: Sign Up for an Anakin.AI Account

Before you can start creating, you'll need an Anakin.AI account.  Here is how to create an Anakin Account

  • Visit Anakin.AI
  • Click on "Launch App"
  • Choose to sign up with your Google account or use an email address.
  • Once signed in, you'll be ready to start your AI app adventure.

Step 2: Create a New App

Your Anakin.AI dashboard is where all the magic happens. To create a new AI app, follow these steps:

  • Once logged in, click "Create app."
  • Give your app a name. Make sure it's something memorable and reflective of your app's purpose.
  • Select the app type as "Workflow." This will enable you to create multi-step processes that can include various AI functions.

Step 3: Setting Up User Inputs

Your AI app needs to interact with users. To set this up:

  • Click on "User Input" in the workflow builder.
  • Add the necessary variables according to how you want your users to provide inputs to your AI.
  • Decide on the type of input fields required such as text, number, or even file uploads depending on your app's function.

Step 4: Designing Your App's Workflow

Now it's time to design the flow of interactions within your app:

  • Click on "Add step" within the workflow builder.
  • Pick from various AI and automation tools to set up each step, like chatbots, voice assistants, and translation services.
  • Arrange the steps in the order you want them to be executed.
  • Ensure the logical flow makes sense and will produce the intended results.

Watch this video for detailed understanding of Anakin workflow

Step 5: Integrating LLaMA 3 API

The heart of your AI app will be the LLaMA 3 AI model.

  • Add the "AI Text Generator" step to your workflow to integrate LLaMA 3 API.
  • Configure the model settings according to the predictions you want in your app.
  • Set up the rest of your workflow steps and their interactions with LLaMA 3 to create a seamless experience.

Step 6: Configuring Your App's Outputs

The last step is to define how your AI app will convey information back to the users.

  • Navigate to the Output section in your workflow.
  • Set the output as the last step output

Congratulations! You've just created an AI app using LLaMA 3 API. From here, you can publish it, integrate it into your website, or share it with the world. The possibilities are as limitless as the power of AI itself.